SleepDiary1Week

A small dataset containing sleep diary data for a single week
and single subject
<ul>
<li>FOLIOCC. unique subject id</li>
<li>etapa.</li>
<li>stage.</li>
<li>start_day. first day of measurement</li>
<li>time_bed1. time at which the subject reported going to sleep on day 1</li>
<li>time_wake1. time at which the subject reported waking up on day 1</li>
<li>time_bed2. time at which the subject reported going to sleep on day 2</li>
<li>time_wake2. time at which the subject reported waking up on day 2</li>
<li>time_bed3. time at which the subject reported going to sleep on day 3</li>
<li>time_wake3. time at which the subject reported waking up on day 3</li>
<li>time_bed4. time at which the subject reported going to sleep on day 4</li>
<li>time_wake4. time at which the subject reported waking up on day 4</li>
<li>time_bed5. time at which the subject reported going to sleep on day 5</li>
<li>time_wake5. time at which the subject reported waking up on day 5</li>
<li>time_bed6. time at which the subject reported going to sleep on day 6</li>
<li>time_wake6. time at which the subject reported waking up on day 6</li>
<li>time_bed7. time at which the subject reported going to sleep on day 7</li>
<li>time_wake7. time at which the subject reported waking up on day 7</li>
</ul>

datasets

Provides sleep duration estimates using a Pruned Dynamic
Programming (PDP) algorithm that efficiently identifies
change-points. PDP applied to physical activity data can identify
transitions from wakefulness to sleep and vice versa. Baek, Jonggyu, Banker,
Margaret, Jansen, Erica C., She, Xichen, Peterson, Karen E., Pitchford,
E. Andrew, Song, Peter X. K. (2021) An Efficient Segmentation Algorithm to
Estimate Sleep Duration from Actigraphy Data <doi:10.1007/s12561-021-09309-3>.

SleepDiary1Week: Sleep Diary 1-Week Data

Description

Usage

Arguments

Format